1. Field of Invention
The present invention relates to a method of processing an image, and more particularly to a method of pre-compressing rate-distortion optimization for JPEG 2000 images, which can reduce the computational power of the entropy encoder and unnecessary memory requirement for a code-steam without losing the quality of the JPEG 2000 image.
2. Description of Related Arts
Joint Photographics Experts Group (JPEG) technique has popularly been utilized for images processing in computer environment. JPEG 2000 is the new still imaging coding standard in next generation. The performance of JPEG 2000 is superior to JPEG at all bit rate. However, the computational complexity of JPEG 2000 is much higher than that of JPEG.
Accordingly, there are two major parts in JPEG 2000: Discrete Wavelet Transform (DWT), and Embedded Block Coding with Optimized Truncation (EBCOT). In general, quantization is not used to control the rate of code-stream in JPEG 2000 encoder. It is applied to adjust weights of different frequency bands based on the filter bank and decomposition level of DWT, and no quantization is used at reversible wavelet transform mode. After DWT and quantization, the coefficients are partitioned into code-blocks, which are encoded by EBCOT. The most complex part in JPEG 2000 is EBCOT. EBCOT is a two-tiered algorithm. Tier-1 is embedded block coder, which utilizes context-based arithmetic coding to encode each code-block into independent embedded bit-stream. Tier-2 is post-compression rate-distortion optimization algorithm. EBCOT Tier-1 is the most complex part of JPEG 2000, which consumes more than 50% of total computation power. Reducing its computation time can significantly decrease the total run time of JPEG 2000 encoder.
Most still image coding standard, including JPEG, use quantization scheme to achieve rate control. However, this scheme cannot provide best quality at a given bit rate and get precise rate in one iteration. Instead of using quantization scheme to perform the rate control, JPEG 2000 uses a better scheme to control the rate by EBCOT Tier-2 processing. It uses Lagrange optimization to precisely control the bit rate and guarantees the best quality at specific bit rate. However, in the rate-distortion optimization, all transformed coefficients must be processed by EBCOT Tier-1 to get the rate and distortion information. In most cases, most compressed bit-streams generated by EBCOT Tier-1 will be discarded through the procedure of EBCOT Tier-2. The memory spent to store the discarded bit-stream and computations used are all wasted. Some previous works focus on memory and power reduction for post-compression optimization scheme. For example, Chang et al., use EBCOT Tier-2 feedback control to terminate redundant computation of EBCOT Tier-1. Computation time of EBCOT Tier-1 can be reduced to 40% and 20% at medium to high compression rate. Yeung proposed a scheme based on priority scanning. It is to encode the truncation points in a different order by priority information and terminate block coding adequately. The computational cost and memory requirement can be reduced by 52% and 71% respectively in the case of 0.25 bpp.